Semantic Query Optimization: Correctness and Control

2006 ◽  
Vol 10 (3) ◽  
pp. 270-280
Author(s):  
Pongtawat Chippimolchai ◽  
◽  
Kiyoshi Akama ◽  
Vilas Wuwongse ◽  
Keyword(s):  
Query Optimization ◽  
Control Strategy ◽  
Semantic Knowledge ◽  
Integrity Constraints ◽  
Equivalent Transformation ◽  
Two Phase ◽  
Semantic Query ◽  
Optimization Framework ◽  
Semantic Query Optimization ◽  
And Control

We developed a semantic query optimization framework for deductive databases based on equivalent transformation (ET) rules. ET rules, prepared from the semantic knowledge of databases, such as integrity constraints, transform given queries into syntactically different but semantically equivalent and more efficient forms. We formally prove the correctness of query transformations by ET rules. For efficiency, we propose a two-phase heuristic-based strategy to guide query transformations and introduce a condition-based control strategy to prevent unwanted, unnecessary transformations. We give examples demonstrating the possible optimization.

scholarly journals SQOPI: Semantic Query Optimization Framework

2014 ◽  
Vol 96 (6) ◽  
pp. 27-32 ◽  
Author(s):  
Mohamed MounirHassan ◽  
Ahmed Mohammed Sultan
Keyword(s):  
Query Optimization ◽  
Semantic Query ◽  
Optimization Framework ◽  
Semantic Query Optimization

Consistent Queries Over Databases with Integrity Constraints

2002 ◽  
pp. 172-202
Author(s):  
Sergio Greco ◽  
Ester Zumpano
Keyword(s):  
Query Optimization ◽  
Information Sources ◽  
Integrity Constraints ◽  
Database Integration ◽  
Functional Dependencies ◽  
Multiple Sources ◽  
Semantic Query ◽  
Cooperative Query Answering ◽  
Semantic Query Optimization ◽  
Source Of Information

Integrity constraints represent an important source of information about the real world. They are usually used to define constraints on data (functional dependencies, inclusion dependencies, etc.). Nowadays integrity constraints have a wide applicability in several contexts such as semantic query optimization, cooperative query answering, database integration and view update. Often databases may be inconsistent with respect to integrity constraints, that is, one or more integrity constraints are not satisfied. This may happen, for instance, when the database is obtained from the integration of different information sources. The integration of knowledge from multiple sources is an important aspect in several areas such as data warehousing, database integration, automated reasoning systems and active reactive databases.

DESIGN AND IMPLEMENTATION OF A KNOWLEDGE-BASED QUERY PROCESSOR

1993 ◽  
Vol 02 (02) ◽  
pp. 107-125 ◽  
Author(s):  
NABIL R. ADAM ◽  
ARYYA GANGOPADHYAY ◽  
JAMES GELLER
Keyword(s):  
Query Optimization ◽  
Relational Databases ◽  
Semantic Knowledge ◽  
Database Management System ◽  
Database Schema ◽  
Semantic Query ◽  
Design And Implementation ◽  
Knowledge Based ◽  
User Query ◽  
Semantic Query Optimization

This paper deals with query processing using semantic knowledge in relational databases. The Select-Project-Join (SPJ) conjunctive class of queries are dealt with in this paper. We propose to optimize highly repetitive queries by using semantic transformations in addition to syntactic transformations. Thus, we generate a set of pre-optimized queries. This set contains queries that are semantically equivalent to, syntactically different from, and more efficient to process than the user queries that we started with. The issues we address in this paper are: how to map a user query to a query that is in the set of pre-optimized and already optimized queries, how to search efficiently through the set of pre-optimized queries and set of semantic rules, and how to incorporate new queries to the set of pre-optimized queries, so that the number of queries that can be optimized using this method increases with the passage of time. Furthermore, we suggest some ideas of handling queries that do not have any semantically equivalent counterpart in the set of pre-optimized queries. We have tested the performance of the proposed method. An algorithm for mapping is implemented in Prolog. A database schema is implemented in the INGRES database management system. We have adopted a database schema that is widely used for measuring performance in the semantic query optimization literature.

Consistent Queries over Databases with Integrity Constraints

2009 ◽  
pp. 2051-2058
Author(s):  
Luciano Caroprese ◽  
Cristian Molinaro ◽  
Irina Trubitsyna ◽  
Ester Zumpano
Keyword(s):  
Integrity Constraints ◽  
Database Integration ◽  
Functional Dependencies ◽  
Distributed Information ◽  
Semantic Query ◽  
Cooperative Query Answering ◽  
Semantic Query Optimization ◽  
Integration Architecture ◽  
Source Of Information ◽  
Different Sources

Integrating data from different sources consists of two main steps, the first in which the various relations are merged together, and the second in which some tuples are removed (or inserted) from the resulting database in order to satisfy integrity constraints. There are several ways to integrate databases or possibly distributed information sources, but whatever integration architecture we choose, the heterogeneity of the sources to be integrated causes subtle problems. In particular, the database obtained from the integration process may be inconsistent with respect to integrity constraints, that is, one or more integrity constraints are not satisfied. Integrity constraints represent an important source of information about the real world. They are usually used to define constraints on data (functional dependencies, inclusion dependencies, etc.) and have, nowadays, a wide applicability in several contexts such as semantic query optimization, cooperative query answering, database integration, and view update.

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